SIVA PRASAD MANDALAPU
AI/ML Engineer
I am an AI/ML Engineer with 5+ years of experience building production-grade machine learning systems across healthcare imaging and financial services. I specialize in the full ML lifecycle — from data engineering and model development to cloud deployment and real-time monitoring. At Philips Healthcare, I lead computer vision pipelines that process over 10,000 chest X-rays daily, achieving 92% anomaly-detection precision, and integrate LLMs to automate radiology report generation. At HDFC Bank, I built NLP-driven fraud detection systems that analyzed over 5 million daily transactions with 95% recall — helping protect customers at scale. I'm experienced across a broad stack, including PyTorch, TensorFlow, Hugging Face Transformers, LangChain, AWS SageMaker, Azure ML, and Kubernetes, with a strong focus on MLOps practices like CI/CD automation, federated learning, and model explainability. I'm passionate about building AI systems that don't just perform in research settings, but solve real problems in production — reliably, responsibly, and at scale.
Experience
AI/ML Engineer (Contract)
Philips Healthcare · Remote.
- Cut diagnostic inference latency 13x, from 2s to 150ms, across 10K+ daily X-ray scans by optimizing PyTorch
- models with TensorRT and rebuilding the serving layer as FastAPI microservices on edge devices backed by AWS
- SageMaker - holding 92% precision.
- Raised lung-disease detection accuracy 28% by fine-tuning ResNet and YOLOv8 on labeled clinical imaging
- datasets and running automated hyperparameter sweeps in Weights & Biases.
- Shortened model release cycles from 4 weeks to 1 week by building end-to-end CI/CD across MLflow, Jenkins, GitHub Actions, Docker, and Kubernetes, making every deployment versioned and reproducible.
- Improved cross-site model generalization 15% with zero patient data leaving origin sites by architecting a
- HIPAA-compliant federated learning pipeline in Flower spanning 5 regional hospital networks.
- Reduced radiologist draft-review time 35% by building an agentic GenAI pipeline - LangChain, LangGraph, and
- RAG over BERT-based LLMs - that generates clinical report drafts directly from imaging model outputs.
- Caught hallucination and drift incidents before release by instrumenting a real-time LLM observability layer with
- LangSmith, Prometheus, and Grafana, paired with bias-detection pipelines and HIPAA fairness dashboards
- documenting model equity across patient subgroups.
- Processed 500GB+ of imaging data per training cycle by orchestrating Apache Spark and Kafka ETL pipelines
- with schema enforcement, automated quality validation, and augmentation.
- Increased team delivery velocity 20% by mentoring 4 engineers on PyTorch model development, MLOps, and
- LLMOps deployment practices.
AI/ML Engineer | Fraud & Risk AI for India’s largest private bank (70M+Customers.)
HDFC Bank · Bengaluru, India.
- Detected fraud at 95% recall across 5M+ daily transactions with sub-100ms scoring by deploying Transformer-
- based NLP models on Azure ML, cutting false positives 30%.
- Reduced fraud losses 35% by engineering LSTM, Transformer, and Graph Neural Network ensembles for
- behavioral anomaly detection over Kafka streaming pipelines.
- Cut fraud-investigation time 40% by implementing SHAP and LIME explainability layers that auto-generated RBI-
- compliant audit reports for risk and compliance teams.
- Held 99.9% SLA uptime through peak banking hours by automating model retraining, drift detection, and rollback
- with MLflow, Kubeflow, and Kubernetes.
- Improved model F1-score 22% by automating feature-engineering ETL across 1M+ labeled transaction records
- using Pandas and Dask.
- Expanded training data 5x without exposing customer records by generating synthetic transaction data under
- differential-privacy constraints, validated against custom fidelity metrics.
- Delivered 3 fraud-AI systems end to end by leading Agile execution across risk, compliance, and engineering
- teams from data ingestion through production deployment.
Skills
Education
M.S., Information Systems
Marist College · Poughkeepsie, NY.
B.Tech, Mechanical Engineering
Sir C.R.R. College of Engineering · India.